package dedup

import (
	"context"
	"fmt"
	"runtime"
	"sync"
	"sync/atomic"
	"time"
)

// PerformanceOptimizer handles performance optimization for deduplication
type PerformanceOptimizer interface {
	// OptimizeProcessing optimizes the deduplication process
	OptimizeProcessing(ctx context.Context, config *OptimizationConfig) error

	// MonitorPerformance monitors and reports performance metrics
	MonitorPerformance(ctx context.Context) (*PerformanceMetrics, error)

	// TuneParameters tunes system parameters for optimal performance
	TuneParameters(ctx context.Context, metrics *PerformanceMetrics) error

	// GetOptimizationStats returns optimization statistics
	GetOptimizationStats() OptimizationStats
}

// OptimizationConfig contains optimization configuration
type OptimizationConfig struct {
	MaxMemoryUsage      int64
	MaxCPUUsage         float64
	MaxProcessingTime   time.Duration
	TargetThroughput    float64
	Parallelism         int
	EnableStreaming     bool
	EnableCompression   bool
	EnablePrefetching   bool
	CacheSize           int64
	BatchSize           int
}

// OptimizationStats contains optimization statistics
type OptimizationStats struct {
	TotalOptimizations   int64
	SuccessfulOptimizations int64
	AverageThroughput    float64
	PeakMemoryUsage      int64
	AverageCPUUsage      float64
	CacheHitRate         float64
	LastOptimization     time.Time
}

// SmartPerformanceOptimizer implements intelligent performance optimization
type SmartPerformanceOptimizer struct {
	mu                sync.RWMutex
	config            OptimizationConfig
	stats             OptimizationStats
	resourceMonitor   *ResourceMonitor
	cacheManager      *CacheManager
	concurrencyController *ConcurrencyController
	streamingProcessor  *StreamingProcessor
	metricsHistory    []PerformanceMetrics
	optimizationRules map[string]OptimizationRule
}

// ResourceMonitor monitors system resources
type ResourceMonitor struct {
	mu              sync.RWMutex
	memoryUsage     int64
	cpuUsage        atomic.Value // float64
	goroutineCount  int32
	diskIO          atomic.Value // float64
	networkIO       atomic.Value // float64
	lastUpdate      time.Time
}

// CacheManager manages intelligent caching
type CacheManager struct {
	mu              sync.RWMutex
	cache           map[string]*CacheEntry
	maxSize         int64
	currentSize     int64
	evictionPolicy  string // "lru", "lfu", "fifo"
	hitCount        int64
	missCount       int64
	stats           CacheStats
}

// CacheEntry represents a cache entry
type CacheEntry struct {
	Key        string
	Data       []byte
	Size       int64
	AccessTime time.Time
	AccessCount int64
	HitCount   int64
}

// CacheStats contains cache statistics
type CacheStats struct {
	HitRate      float64
	EvictionCount int64
	EntryCount   int64
	TotalSize    int64
}

// ConcurrencyController manages concurrent processing
type ConcurrencyController struct {
	mu              sync.RWMutex
	maxWorkers      int
	activeWorkers   int32
	taskQueue       chan Task
	resultQueue     chan Result
	workerPool      []*Worker
	adaptiveMode    bool
	performanceHistory []float64
}

// Task represents a deduplication task
type Task struct {
	ID          string
	Type        string // "file", "block", "batch"
	Data        interface{}
	Priority    int
	Timeout     time.Duration
	Metadata    map[string]interface{}
}

// Result represents a task result
type Result struct {
	TaskID   string
	Success  bool
	Data     interface{}
	Error    error
	Duration time.Duration
	Metrics  TaskMetrics
}

// TaskMetrics contains task performance metrics
type TaskMetrics struct {
	ProcessingTime time.Duration
	MemoryUsage    int64
	CPUUsage       float64
	Throughput     float64
}

// Worker represents a concurrent worker
type Worker struct {
	ID         int
	TaskQueue  <-chan Task
	ResultQueue chan<- Result
	Active     atomic.Bool
	Metrics    WorkerMetrics
}

// WorkerMetrics contains worker performance metrics
type WorkerMetrics struct {
	TasksProcessed int64
	TotalTime      time.Duration
	AverageTime    time.Duration
	ErrorCount     int64
	LastTaskTime   time.Time
}

// StreamingProcessor handles streaming data processing
type StreamingProcessor struct {
	mu              sync.RWMutex
	bufferSize      int
	batchSize       int
	pipelineDepth   int
	processors      []DataProcessor
	inputChan       chan []byte
	outputChan      chan ProcessingResult
	metrics         StreamingMetrics
}

// DataProcessor represents a data processing stage
type DataProcessor interface {
	Process(ctx context.Context, data []byte) ([]byte, error)
	GetName() string
	GetMetrics() ProcessorMetrics
}

// ProcessingResult represents processing result
type ProcessingResult struct {
	Data      []byte
	Metadata  map[string]interface{}
	Error     error
	Duration  time.Duration
}

// StreamingMetrics contains streaming performance metrics
type StreamingMetrics struct {
	TotalProcessed   int64
	Throughput       float64
	AverageLatency   time.Duration
	PipelineUtilization float64
	BackpressureTime time.Duration
}

// ProcessorMetrics contains processor metrics
type ProcessorMetrics struct {
	ProcessedCount int64
	ErrorCount     int64
	AverageTime    time.Duration
	Throughput     float64
}

// NewSmartPerformanceOptimizer creates a new performance optimizer
func NewSmartPerformanceOptimizer(config OptimizationConfig) (*SmartPerformanceOptimizer, error) {
	if config.Parallelism <= 0 {
		config.Parallelism = runtime.NumCPU()
	}

	if config.BatchSize <= 0 {
		config.BatchSize = 100
	}

	optimizer := &SmartPerformanceOptimizer{
		config:            config,
		stats:             OptimizationStats{},
		resourceMonitor:   NewResourceMonitor(),
		metricsHistory:    make([]PerformanceMetrics, 0, 1000),
		optimizationRules: initializeOptimizationRules(),
	}

	// Initialize cache manager
	optimizer.cacheManager = NewCacheManager(config.CacheSize, "lru")

	// Initialize concurrency controller
	optimizer.concurrencyController = NewConcurrencyController(config.Parallelism, true)

	// Initialize streaming processor if enabled
	if config.EnableStreaming {
		optimizer.streamingProcessor = NewStreamingProcessor(config.BatchSize, 3)
	}

	return optimizer, nil
}

// OptimizeProcessing optimizes the deduplication process
func (o *SmartPerformanceOptimizer) OptimizeProcessing(ctx context.Context, config *OptimizationConfig) error {
	o.mu.Lock()
	defer o.mu.Unlock()

	startTime := time.Now()

	// Monitor current performance
	currentMetrics, err := o.MonitorPerformance(ctx)
	if err != nil {
		return fmt.Errorf("failed to monitor performance: %w", err)
	}

	// Apply optimization rules
	if err := o.applyOptimizationRules(ctx, currentMetrics); err != nil {
		return fmt.Errorf("failed to apply optimization rules: %w", err)
	}

	// Tune parameters based on metrics
	if err := o.TuneParameters(ctx, currentMetrics); err != nil {
		return fmt.Errorf("failed to tune parameters: %w", err)
	}

	// Update statistics
	o.stats.TotalOptimizations++
	o.stats.SuccessfulOptimizations++
	o.stats.LastOptimization = time.Now()

	optimizationTime := time.Since(startTime)
	if optimizationTime > 0 {
		o.stats.AverageThroughput = float64(currentMetrics.Throughput) / optimizationTime.Seconds()
	}

	return nil
}

// MonitorPerformance monitors and reports performance metrics
func (o *SmartPerformanceOptimizer) MonitorPerformance(ctx context.Context) (*PerformanceMetrics, error) {
	// Get resource usage
	resourceMetrics := o.resourceMonitor.GetMetrics()

	// Get cache statistics
	cacheMetrics := o.cacheManager.GetStats()

	// Get concurrency statistics
	concurrencyMetrics := o.concurrencyController.GetMetrics()

	// Get streaming statistics (if enabled)
	_ = o.streamingProcessor // Use the streaming processor if needed in future

	metrics := &PerformanceMetrics{
		Timestamp:        time.Now(),
		Algorithm:        "smart_optimizer",
		ProcessingTime:   time.Since(resourceMetrics.StartTime),
		MemoryUsage:      resourceMetrics.MemoryUsage,
		CPUUsage:         resourceMetrics.CPUUsage,
		DeduplicationRatio: cacheMetrics.HitRate,
		Throughput:       concurrencyMetrics.Throughput,
		ErrorRate:        concurrencyMetrics.ErrorRate,
		CacheHitRate:     cacheMetrics.HitRate,
	}

	// Store in history
	o.metricsHistory = append(o.metricsHistory, *metrics)
	if len(o.metricsHistory) > 1000 {
		o.metricsHistory = o.metricsHistory[1:]
	}

	return metrics, nil
}

// TuneParameters tunes system parameters for optimal performance
func (o *SmartPerformanceOptimizer) TuneParameters(ctx context.Context, metrics *PerformanceMetrics) error {
	// Tune concurrency level
	if err := o.tuneConcurrency(metrics); err != nil {
		return fmt.Errorf("failed to tune concurrency: %w", err)
	}

	// Tune cache size
	if err := o.tuneCacheSize(metrics); err != nil {
		return fmt.Errorf("failed to tune cache size: %w", err)
	}

	// Tune batch size
	if err := o.tuneBatchSize(metrics); err != nil {
		return fmt.Errorf("failed to tune batch size: %w", err)
	}

	return nil
}

// GetOptimizationStats returns optimization statistics
func (o *SmartPerformanceOptimizer) GetOptimizationStats() OptimizationStats {
	o.mu.RLock()
	defer o.mu.RUnlock()

	return o.stats
}

// applyOptimizationRules applies intelligent optimization rules
func (o *SmartPerformanceOptimizer) applyOptimizationRules(ctx context.Context, metrics *PerformanceMetrics) error {
	for ruleName, rule := range o.optimizationRules {
		if rule.Condition(metrics) {
			if err := rule.Action(ctx, o); err != nil {
				return fmt.Errorf("failed to apply rule %s: %w", ruleName, err)
			}
		}
	}
	return nil
}

// tuneConcurrency tunes concurrency level based on performance
func (o *SmartPerformanceOptimizer) tuneConcurrency(metrics *PerformanceMetrics) error {
	// Simple adaptive concurrency tuning
	if metrics.CPUUsage < 0.3 && metrics.Throughput < o.config.TargetThroughput {
		// Increase concurrency
		o.concurrencyController.IncreaseWorkers(1)
	} else if metrics.CPUUsage > 0.8 {
		// Decrease concurrency
		o.concurrencyController.DecreaseWorkers(1)
	}

	return nil
}

// tuneCacheSize tunes cache size based on performance
func (o *SmartPerformanceOptimizer) tuneCacheSize(metrics *PerformanceMetrics) error {
	if metrics.CacheHitRate < 0.5 && metrics.MemoryUsage < int64(float64(o.config.MaxMemoryUsage)*0.7) {
		// Increase cache size if hit rate is low and memory is available
		o.cacheManager.Resize(int64(float64(o.config.CacheSize) * 1.2))
	} else if metrics.CacheHitRate > 0.9 && metrics.MemoryUsage > int64(float64(o.config.MaxMemoryUsage)*0.9) {
		// Decrease cache size if hit rate is high and memory is constrained
		o.cacheManager.Resize(int64(float64(o.config.CacheSize) * 0.8))
	}

	return nil
}

// tuneBatchSize tunes batch size based on performance
func (o *SmartPerformanceOptimizer) tuneBatchSize(metrics *PerformanceMetrics) error {
	if metrics.Throughput < o.config.TargetThroughput && metrics.ErrorRate < 0.01 {
		// Increase batch size if throughput is low and error rate is good
		o.config.BatchSize = int(float64(o.config.BatchSize) * 1.1)
		if o.config.BatchSize > 1000 {
			o.config.BatchSize = 1000
		}
	} else if metrics.ErrorRate > 0.05 {
		// Decrease batch size if error rate is high
		o.config.BatchSize = int(float64(o.config.BatchSize) * 0.9)
		if o.config.BatchSize < 10 {
			o.config.BatchSize = 10
		}
	}

	return nil
}

// NewResourceMonitor creates a new resource monitor
func NewResourceMonitor() *ResourceMonitor {
	monitor := &ResourceMonitor{
		lastUpdate: time.Now(),
	}

	// Initialize cpuUsage with a default value
	monitor.cpuUsage.Store(0.0)

	// Start monitoring goroutine
	go monitor.monitorLoop()

	return monitor
}

// monitorLoop continuously monitors system resources
func (rm *ResourceMonitor) monitorLoop() {
	ticker := time.NewTicker(1 * time.Second)
	defer ticker.Stop()

	for range ticker.C {
		rm.updateMetrics()
	}
}

// updateMetrics updates resource usage metrics
func (rm *ResourceMonitor) updateMetrics() {
	rm.mu.Lock()
	defer rm.mu.Unlock()

	// Update memory usage
	var m runtime.MemStats
	runtime.ReadMemStats(&m)
	rm.memoryUsage = int64(m.Alloc)

	// Update CPU usage (simplified)
	rm.cpuUsage.Store(0.5) // Placeholder

	// Update goroutine count
	rm.goroutineCount = int32(runtime.NumGoroutine())

	rm.lastUpdate = time.Now()
}

// GetMetrics returns current resource metrics
func (rm *ResourceMonitor) GetMetrics() ResourceMetrics {
	rm.mu.RLock()
	defer rm.mu.RUnlock()

	return ResourceMetrics{
		MemoryUsage:    rm.memoryUsage,
		CPUUsage:       rm.cpuUsage.Load().(float64),
		GoroutineCount: rm.goroutineCount,
		StartTime:      rm.lastUpdate,
	}
}

// ResourceMetrics contains resource usage metrics
type ResourceMetrics struct {
	MemoryUsage    int64
	CPUUsage       float64
	GoroutineCount int32
	StartTime      time.Time
}

// NewCacheManager creates a new cache manager
func NewCacheManager(maxSize int64, evictionPolicy string) *CacheManager {
	return &CacheManager{
		cache:          make(map[string]*CacheEntry),
		maxSize:        maxSize,
		evictionPolicy: evictionPolicy,
		stats:          CacheStats{},
	}
}

// Get retrieves data from cache
func (cm *CacheManager) Get(key string) ([]byte, bool) {
	cm.mu.RLock()
	defer cm.mu.RUnlock()

	if entry, exists := cm.cache[key]; exists {
		entry.AccessTime = time.Now()
		entry.AccessCount++
		atomic.AddInt64(&cm.hitCount, 1)
		return entry.Data, true
	}

	atomic.AddInt64(&cm.missCount, 1)
	return nil, false
}

// Set stores data in cache
func (cm *CacheManager) Set(key string, data []byte) error {
	cm.mu.Lock()
	defer cm.mu.Unlock()

	dataSize := int64(len(data))

	// Check if we need to evict entries
	if cm.currentSize+dataSize > cm.maxSize {
		cm.evictEntries(dataSize)
	}

	entry := &CacheEntry{
		Key:        key,
		Data:       data,
		Size:       dataSize,
		AccessTime: time.Now(),
		AccessCount: 1,
	}

	cm.cache[key] = entry
	cm.currentSize += dataSize
	cm.stats.EntryCount++
	cm.stats.TotalSize += dataSize

	return nil
}

// GetStats returns cache statistics
func (cm *CacheManager) GetStats() CacheStats {
	cm.mu.RLock()
	defer cm.mu.RUnlock()

	hitCount := atomic.LoadInt64(&cm.hitCount)
	missCount := atomic.LoadInt64(&cm.missCount)
	total := hitCount + missCount

	if total > 0 {
		cm.stats.HitRate = float64(hitCount) / float64(total)
	}

	return cm.stats
}

// Resize resizes the cache
func (cm *CacheManager) Resize(newSize int64) {
	cm.mu.Lock()
	defer cm.mu.Unlock()

	cm.maxSize = newSize

	// Evict entries if necessary
	if cm.currentSize > cm.maxSize {
		cm.evictEntries(cm.currentSize - cm.maxSize)
	}
}

// evictEntries evicts entries based on the eviction policy
func (cm *CacheManager) evictEntries(targetSize int64) {
	// Simple LRU eviction
	var oldestKey string
	var oldestTime time.Time

	for key, entry := range cm.cache {
		if oldestKey == "" || entry.AccessTime.Before(oldestTime) {
			oldestKey = key
			oldestTime = entry.AccessTime
		}
	}

	if oldestKey != "" {
		if entry, exists := cm.cache[oldestKey]; exists {
			cm.currentSize -= entry.Size
			delete(cm.cache, oldestKey)
			cm.stats.EntryCount--
			cm.stats.TotalSize -= entry.Size
			cm.stats.EvictionCount++
		}
	}
}

// NewConcurrencyController creates a new concurrency controller
func NewConcurrencyController(maxWorkers int, adaptiveMode bool) *ConcurrencyController {
	return &ConcurrencyController{
		maxWorkers:         maxWorkers,
		taskQueue:          make(chan Task, maxWorkers*2),
		resultQueue:        make(chan Result, maxWorkers*2),
		workerPool:         make([]*Worker, 0, maxWorkers),
		adaptiveMode:       adaptiveMode,
		performanceHistory: make([]float64, 0, 100),
	}
}

// Start starts the concurrency controller
func (cc *ConcurrencyController) Start(ctx context.Context) error {
	// Initialize workers
	for i := 0; i < cc.maxWorkers; i++ {
		worker := &Worker{
			ID:          i,
			TaskQueue:   cc.taskQueue,
			ResultQueue: cc.resultQueue,
		}
		cc.workerPool = append(cc.workerPool, worker)
		go worker.Start(ctx)
	}

	return nil
}

// Submit submits a task for processing
func (cc *ConcurrencyController) Submit(task Task) error {
	select {
	case cc.taskQueue <- task:
		return nil
	default:
		return fmt.Errorf("task queue is full")
	}
}

// GetResult gets a result from the result queue
func (cc *ConcurrencyController) GetResult() (Result, bool) {
	select {
	case result := <-cc.resultQueue:
		return result, true
	default:
		return Result{}, false
	}
}

// IncreaseWorkers increases the number of workers
func (cc *ConcurrencyController) IncreaseWorkers(delta int) {
	cc.mu.Lock()
	defer cc.mu.Unlock()

	// Implementation would add new workers
}

// DecreaseWorkers decreases the number of workers
func (cc *ConcurrencyController) DecreaseWorkers(delta int) {
	cc.mu.Lock()
	defer cc.mu.Unlock()

	// Implementation would remove workers
}

// GetMetrics returns concurrency metrics
func (cc *ConcurrencyController) GetMetrics() ConcurrencyMetrics {
	cc.mu.RLock()
	defer cc.mu.RUnlock()

	return ConcurrencyMetrics{
		ActiveWorkers: int32(len(cc.workerPool)),
		QueueSize:     int32(len(cc.taskQueue)),
		Throughput:    0, // Calculate based on recent performance
		ErrorRate:     0, // Calculate based on recent errors
	}
}

// ConcurrencyMetrics contains concurrency performance metrics
type ConcurrencyMetrics struct {
	ActiveWorkers int32
	QueueSize     int32
	Throughput    float64
	ErrorRate     float64
}

// Start starts the worker
func (w *Worker) Start(ctx context.Context) {
	w.Active.Store(true)
	defer w.Active.Store(false)

	for {
		select {
		case <-ctx.Done():
			return
		case task := <-w.TaskQueue:
			w.processTask(ctx, task)
		}
	}
}

// processTask processes a task
func (w *Worker) processTask(ctx context.Context, task Task) {
	startTime := time.Now()

	// Process the task (simplified)
	result := Result{
		TaskID:   task.ID,
		Success:  true,
		Duration: time.Since(startTime),
		Metrics: TaskMetrics{
			ProcessingTime: time.Since(startTime),
			MemoryUsage:    1024, // Placeholder
			CPUUsage:       0.1,  // Placeholder
			Throughput:     1024, // Placeholder
		},
	}

	w.Metrics.TasksProcessed++
	w.Metrics.TotalTime += result.Duration
	w.Metrics.LastTaskTime = time.Now()

	w.ResultQueue <- result
}

// NewStreamingProcessor creates a new streaming processor
func NewStreamingProcessor(batchSize int, pipelineDepth int) *StreamingProcessor {
	return &StreamingProcessor{
		bufferSize:    batchSize,
		batchSize:     batchSize,
		pipelineDepth: pipelineDepth,
		processors:    make([]DataProcessor, 0),
		inputChan:     make(chan []byte, pipelineDepth),
		outputChan:    make(chan ProcessingResult, pipelineDepth),
	}
}

// GetMetrics returns streaming metrics
func (sp *StreamingProcessor) GetMetrics() *StreamingMetrics {
	sp.mu.RLock()
	defer sp.mu.RUnlock()

	return &sp.metrics
}

// initializeOptimizationRules initializes optimization rules
func initializeOptimizationRules() map[string]OptimizationRule {
	rules := make(map[string]OptimizationRule)

	// High memory usage rule
	rules["high_memory"] = OptimizationRule{
		Condition: func(metrics *PerformanceMetrics) bool {
			return metrics.MemoryUsage > 1024*1024*1024 // 1GB
		},
		Action: func(ctx context.Context, optimizer *SmartPerformanceOptimizer) error {
			// Reduce cache size and concurrency
			optimizer.cacheManager.Resize(512 * 1024 * 1024) // 512MB
			optimizer.concurrencyController.DecreaseWorkers(2)
			return nil
		},
	}

	// High CPU usage rule
	rules["high_cpu"] = OptimizationRule{
		Condition: func(metrics *PerformanceMetrics) bool {
			return metrics.CPUUsage > 0.8
		},
		Action: func(ctx context.Context, optimizer *SmartPerformanceOptimizer) error {
			// Reduce concurrency
			optimizer.concurrencyController.DecreaseWorkers(1)
			return nil
		},
	}

	// Low cache hit rate rule
	rules["low_cache_hit"] = OptimizationRule{
		Condition: func(metrics *PerformanceMetrics) bool {
			return metrics.CacheHitRate < 0.3
		},
		Action: func(ctx context.Context, optimizer *SmartPerformanceOptimizer) error {
			// Increase cache size if memory allows
			currentMetrics := optimizer.GetMetrics()
			if currentMetrics.MemoryUsage < 512*1024*1024 { // 512MB
				optimizer.cacheManager.Resize(1024 * 1024 * 1024) // 1GB
			}
			return nil
		},
	}

	return rules
}

// GetMetrics returns current performance metrics (placeholder implementation)
func (o *SmartPerformanceOptimizer) GetMetrics() PerformanceMetrics {
	return PerformanceMetrics{
		Timestamp:        time.Now(),
		Algorithm:        "smart_optimizer",
		ProcessingTime:   0,
		MemoryUsage:      0,
		CPUUsage:         0,
		DeduplicationRatio: 0,
		Throughput:       0,
		ErrorRate:        0,
		CacheHitRate:     0,
	}
}

// OptimizationRule represents an optimization rule
type OptimizationRule struct {
	Condition func(*PerformanceMetrics) bool
	Action    func(context.Context, *SmartPerformanceOptimizer) error
}